# -*- coding: utf-8 -*-
from datetime import timedelta
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator

from jms_hi.dm.dm_deliver_sign_hour_detail_dt import jms_dm__dm_deliver_sign_hour_detail_dt

jms_dm__dm_deliver_sign_hour_sum_dt = SparkSqlOperator(
    task_id='jms_dm__dm_deliver_sign_hour_sum_dt',
    task_concurrency=1,
    pool_slots=2,
    master='yarn',
    execution_timeout=timedelta(hours=1),
    depends_on_past=True,
    email=['houwenlong@jtexpress.com','yl_bigdata@yl-scm.com'],
    name='jms_dm__dm_deliver_sign_hour_sum_dt_{{ execution_date |hour_add(1)| cst_hour }}',
    sql='jms_hi/dm/dm_deliver_sign_hour_sum_dt/execute.hql',
    driver_memory='5G' , 
    driver_cores=4 , 
    executor_cores=3 ,
    executor_memory='4G' ,
    num_executors=3 , 
    conf={
        'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
        'spark.shuffle.service.enabled': 'true',  # 动态资源 Shuffle 服务开启
        'spark.dynamicAllocation.maxExecutors'             : 8 ,
        'spark.dynamicAllocation.cachedExecutorIdleTimeout': 120,  # 动态资源自动释放闲置 Executor 的超时时间(s)
        'spark.executor.memoryOverhead'             : '2G' , 
        'spark.hadoop.hive.exec.dynamic.partition.mode': 'nonstrict', # 动态分区
        'spark.hadoop.hive.exec.dynamic.partition': 'true'
    },
    yarn_queue='pro',
)

jms_dm__dm_deliver_sign_hour_sum_dt << [
    jms_dm__dm_deliver_sign_hour_detail_dt
]
